Probabilistic load flow using latin hypercube sampling with dependence for distribution networks

The paper adopts the Latin Hypercube Sampling with Dependence (LHSD) method to solve the Probabilistic Load Flow (PLF) problem with correlated random variables for distribution networks. The proposed method is investigated using modified IEEE 34 distribution system with random loads, Wind power and Photovoltaics (PVs). Three different cases are studied and the comparison results shows that the LHSD method handles correlations efficiently and presents an accurate simulation result with a much smaller simulation size. The method has the potential to be applied in many power system probabilistic problems.